The Caatinga dry forest encompasses 11% of the total continental territory of Brazil. Nevertheless, most research on the relationship between phenology and ecosystem productivity of Brazilian tropical forests is aimed at the Amazon basin. Thus, in this study we evaluated the seasonality of ecosystem productivity (gross primary production—GPP) in a preserved Caatinga environment in northeast Brazil. Analyses were carried out using eddy covariance measurements and satellite-derived data from sensor MODIS (MODerate Resolution Imaging Spectroradiometer, MOD17 and MOD13 products). In addition to GPP, we investigated water use efficiency (WUE) and meteorological and phenological aspects through remotely sensed vegetation indices (NDVI and EVI). We verified that ecosystem productivity is limited mainly by evapotranspiration, with maximum GPP values registered in the wetter months, indicating a strong dependency on water availability. NDVI and EVI were positively associated with GPP (r = 0.69 and 0.81, respectively), suggesting a coupling between the emergence of new leaves and the phenology of local photosynthetic capacity. WUE, on the other hand, was strongly controlled by consecutive dry days and not necessarily by total precipitation amount. The vegetation indices adequately described interannual variations of the forest response to environmental factors, and GPP MODIS presented a good relationship with tower-measured GPP in dry (R² = 0.76) and wet (R² = 0.62) periods.

The São Francisco River basin is one of the largest in the Brazilian territory. This basin has enormous economic, social and cultural importance for the country. Its water is used for human and animal supply, irrigation and energy production. This basin is located in an area with different climatic characteristics (humid and semiarid) and studies related to precipitation are very important in this region. In this scenario, the objective of this investigation is to present an assessment of rainfall estimated through the Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (IMERG) product compared with rain gauges over the São Francisco river basin in Brazil. For that, a period from of 20 years and 18 surface weather stations were used to evaluate the product. Based on different evaluation techniques, the study found that the IMERG is appropriate to represent precipitation over the basin. According to the results, the performance of the IMERG product depends on the location where the rain occurs. The bias ranged from −1.67 to 0.34 mm, the RMSE ranged from 5.36 to 10.36 mm and the values of the correlation coefficients between the daily data from the IMERG and rain gauge ranged from 0.28 to 0.61. The results obtained by Student t-test, density curves and regression analysis, in general, show that the IMERG is able to satisfactorily represent rain gauge data. The exception is the eastern portion of the basin, where the product, on average, underestimates the precipitation (p-value < 0.05) and presents the worst statistical metrics.

Climate extreme events are becoming increasingly frequent worldwide, causing floods, drought, forest fires, landslides and heat or cold waves. Several studies have been developed on the assessment of trends in the occurrence of extreme events. However, most of these studies used traditional models, such as Poisson or negative binomial models. Thus, the main objective of this study is to use a space–time data counting approach in the modeling of the number of days with extreme precipitation as an alternative to the commonly used statistical methods. The study area is the Northeast Brazil region, and the analysis was carried out for the period between 1 January 1980 and 31 December 2010, by assessing the frequency of extreme precipitation represented by the R10 mm, R20 mm and R* indices.